Tools for kinetic modeling of biochemical networks

Alves, Rui; Antunes, Fernando; Salvador, Armindo

doi:10.1038/nbt0606-667

Cited by 160 publications

(88 citation statements)

References 15 publications

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“…These languages, which are subsets of the eXtensible Markup Language (XML), support the description of model equations and parameters in machine readable form. Of course, CellML, SBML, and NeuroML model description documents must be validated on creation, but once they have been, they can be disseminated in an error-free way and input to a number of different simulation tools for execution (Alves and Antunes, 2006; Keating et al, 2006). A number of different model repositories such as and the BioModels Database (Li et al, 2010) have been developed that allow users to search for and download XML model descriptions.…”

Section: Informatics In Computational Physiology and Medicinementioning

confidence: 99%

Grand Challenges in Computational Physiology and Medicine

Winslow¹

2011

Front. Physio.

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Section: Informatics In Computational Physiology and Medicinementioning

confidence: 99%

Grand Challenges in Computational Physiology and Medicine

Winslow¹

2011

Front. Physio.

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“…Generalised representation of metabolic and other biochemical models SBML ( [33]; http://www.sbml.org/; see also Table 1 for other Internet resources) is an eXtensible Markup Language (XML) that, in its present version, enables one straightforwardly to describe a biological network and its local equations in a manner that can be exchanged between any number of modelling systems, including what is probably [34] the most popular modelling software, viz. Gepasi [35].…”

Section: Metabolic Reconstruction Is Now Mature and Timelymentioning

confidence: 99%

Systems biology, metabolic modelling and metabolomics in drug discovery and development

Kell

2006

Drug Discovery Today

264

163

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Unlike signalling pathways, metabolic networks are subject to strict stoichiometric constraints. Metabolomics amplifies changes in the proteome, and represents more closely the phenotype of an organism. Recent advances enable the production (and computer-readable encoding as SBML) of metabolic network models reconstructed from genome sequences, as well as experimental measurements of much of the metabolome. There is increasing convergence between the number of human metabolites estimated via genomics ( 3000) and the number measured experimentally. It is thus both timely, and now possible, to bring these two approaches together as an integrated (if distributed) whole to help understand the genesis of metabolic biomarkers, the progress of disease, and the modes of action, efficacy, off-target effects and toxicity of pharmaceutical drugs. Systems biology and metabolic modelling in the 21st CenturyAlthough there are many individual definitions, most commentators (including this one [1,2]) take it that systems biology involves an iterative interplay between more or less high-throughput and high-content 'wet' experiments, technology development, theory and computational modelling, and that it is the involvement of computational modelling, in particular, in the process that sets systems biology apart from the more traditional and more reductionist molecular biology. Metabolomics illustrates this amply. There is also the view that the perceived decrease in the effectiveness of the target-based drug discovery process [3][4][5], including the still-high levels of attrition [6], means that we must move towards understanding organisms at something more akin to a whole-system level [7][8][9][10][11].The question then arises as to what part of a system one might first beneficially model? Although there has, unsurprisingly, been considerable interest in modelling the major signalling pathways (e.g. Refs [12,13]), there are several reasons why it is timely to turn our attention to the level of small molecule metabolism, which is the focus of this review. Metabolism is more discriminatingIt has long been known, and proven through the formalism of metabolic control analysis [7,10,[14][15][16], that whereas small changes in the concentrations of enzymes (and the transcripts that encode them) have only small effects on the fluxes through metabolic pathways, they have substantial effects on the concentrations of metabolic intermediates. Because the metabolome (nominally the concentrations of 'all' the metabolites measured in a system of interest [17]) is downstream of the proteome, it is thereby 'amplified' both in theory [18] and in practice [19,20] and represents a more sensitive level of organisation than do the macromolecular 'omes for understanding a complex biological system, and the changes in it that might be occasioned by disease or pharmaceutical intervention [21,22]. Metabolic reconstruction is now mature and timelyAn attractive feature for the purposes of modelling is that metabolism, in contrast to signalling pathways, ...

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“…Dizzy, BioNetS and RMBNToolbox are network kinetics simulators [88][89][90] (Table 1). The functions and performances of 12 different modeling tools have been compared in detail [91]. Free, ready-to-use and user-friendly software will soon be available for other analysis and modeling approaches.…”

Section: An Outlookmentioning

confidence: 99%